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Relevant bibliographies by topics / Mapping Algorithm

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Academic literature on the topic 'Mapping Algorithm'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Mapping Algorithm"

1

Seliverstov, E. Yu. "Structural Mapping of Global Optimization Algorithms to Graphics Processing Unit Architecture." Herald of the Bauman Moscow State Technical University. Series Instrument Engineering, no. 2 (139) (June 2022): 42–59. http://dx.doi.org/10.18698/0236-3933-2022-2-42-59.

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Graphics processing units (GPU) deliver a high execution efficiency for modern metaheuristic algorithms with a high computation complexity. It is crucial to have an optimal task mapping of the optimization algorithm to the parallel system architecture which strongly affects the efficiency of the optimization process. The paper proposes a novel task mapping algorithm of the parallel metaheuristic algorithm to the GPU architecture, describes problem statement for the mapping of algorithm graph model to the GPU model, and gives a formal definition of graph mapping and mapping restrictions. The al

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BAIYA, SUPARAT, and KASAMSUK UNGCHITTRAKOOL. "Modified inertial Mann’s algorithm and inertial hybrid." Carpathian Journal of Mathematics 39, no. 1 (2022): 27–43. http://dx.doi.org/10.37193/cjm.2023.01.02.

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"In this work, we introduce and study the modified inertial Mann’s algorithm and inertial hybrid algorithm for approximating some fixed points of a k-strict pseudo-contractive mapping in Hilbert spaces. Weak convergence to a solution of fixed-point problems for a k-strict pseudo-contractive mapping is obtained by using the modified inertial Mann’s algorithm. In order to obtain strong convergence, we introduce an inertial hybrid algorithm by using the inertial extrapolation method mixed with the convex combination of three iterated vectors and forcing for strong convergence by the hybrid projec

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Younis, Mudasir, Aadil Dar, and Nawab Hussain. "Revised algorithm for finding a common solution of variational inclusion and fixed point problems." Filomat 37, no. 20 (2023): 6949–60. http://dx.doi.org/10.2298/fil2320949y.

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Recent research has uncovered an algorithm for locating the common solution to variational inclusion problems with multivalued maximal monotone mapping and ?-inverse strongly monotone mapping, as well as the points that are invariant under non-expansive mapping. In their algorithm, Zhang et al. [S. Zhang, J. H. W. Lee, C. K. Chan, Algorithms of common solutions to quasi-variational inclusion and fixed point problems, Appl. Math. Mech. 29(5) (2008), 571-581.], ? must satisfy a very strict condition, namely ? ? [0, 2?]; thus, it cannot be used for all Lipschitz continuous mappings, despite the f

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CHUNG, I.-HSIN, CHE-RUNG LEE, JIAZHENG ZHOU, and YEH-CHING CHUNG. "HIERARCHICAL MAPPING FOR HPC APPLICATIONS." Parallel Processing Letters 21, no. 03 (2011): 279–99. http://dx.doi.org/10.1142/s0129626411000229.

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As the high performance computing systems scale up, mapping the tasks of a parallel application onto physical processors to allow efficient communication becomes one of the critical performance issues. Existing algorithms were usually designed to map applications with regular communication patterns. Their mapping criterion usually overlooks the size of communicated messages, which is the primary factor of communication time. In addition, most of their time complexities are too high to process large scale problems. In this paper, we present a hierarchical mapping algorithm (HMA), which is capab

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He, Tengyuan, Weijun Lu, and Pengju Li. "Fast mapping algorithm with optimized placement selection for CGRA." Journal of Physics: Conference Series 2849, no. 1 (2024): 012106. http://dx.doi.org/10.1088/1742-6596/2849/1/012106.

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Abstract In the field of parallel computing, Coarse-Grained Reconfigurable Architecture (CGRA) is a promising technique for processing parallel applications. Application kernels are mapped on CGRA through the calculation of mapping algorithms. This paper presents a Fast Mapping Algorithm with Optimized Placement Selection for mapping application kernels on CGRAs. The mapping algorithm incorporates heuristic optimizations for processing element (PE) selection based on Hycube Mapping Algorithm and reduces the redundant extra calculation procedures to achieve fast DFG mapping. In algorithm tests

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Aleomraninejad, Seyed, Kanokwan Sitthithakerngkiet, and Poom Kumam. "Hybrid subgradient algorithm for equilibrium and fixed point problems by approximation of nonexpansive mapping." Filomat 34, no. 5 (2020): 1721–29. http://dx.doi.org/10.2298/fil2005721a.

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In this paper anew algorithm considered on a real Hilbert space for finding acommonpoint in the solution set of a class of pseudomonotone equilibrium problem and the set of fixed points of nonexpansive mappings. We produce this algorithm by mappings Tk that are approximations of non-expansive mapping T. The strong convergence theorem of the proposed algorithms is investigated. Our results generalize some recent results in the literature.

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Shrivas, Jaynendra, Rohit Kumar Verma, and Priya Chandraker. "On fixed point convergence results for class of nonexpansivemappings in hyperbolic spaces via PJ iteration process." International Journal of Applied Mathematical Research 13, no. 1 (2024): 12–19. http://dx.doi.org/10.14419/2wamtj79.

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In this paper, we provide certain fixed point results for a mean nonexpansive mapping, as well as a new iterative algorithm called PJ-iterationfor approximating the fixed point of this class of mappings in the setting of hyperbolic spaces. Furthermore, we establish strong and∆-convergence theorem for mean nonexpansive mapping in hyperbolic space. Finally, we present a numerical example to illustrate ourmain result and then display the efficiency of the proposed algorithm compared to different iterative algorithms in the literature. Our resultsobtained in this paper improve, extend and unify so

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Komatsu, Yuki, and Pierre Jais. "Practical Mapping Algorithm." Cardiac Electrophysiology Clinics 5, no. 2 (2013): 161–68. http://dx.doi.org/10.1016/j.ccep.2013.01.008.

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Villaseñor, Carlos, Nancy Arana-Daniel, Alma Alanis, Carlos Lopez-Franco, and Javier Gomez-Avila. "Multiellipsoidal Mapping Algorithm." Applied Sciences 8, no. 8 (2018): 1239. http://dx.doi.org/10.3390/app8081239.

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The robotic mapping problem, which consists in providing a spatial model of the environment to a robot, is a research topic with a wide range of applications. One important challenge of this problem is to obtain a map that is information-rich (i.e., a map that preserves main structures of the environment and object shapes) yet still has a low memory cost. Point clouds offer a highly descriptive and information-rich environmental representation; accordingly, many algorithms have been developed to approximate point clouds and lower the memory cost. In recent years, approaches using basic and “si

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Niu, Xiaoqiang, Hao Lan, and Dan Zeng. "Research on Intelligent Mapping Algorithm of Secure Virtual Network under Cloud Computing." Wireless Communications and Mobile Computing 2022 (May 9, 2022): 1–10. http://dx.doi.org/10.1155/2022/4976176.

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In order to improve the mapping efficiency of network intelligent mapping algorithm, this paper proposes a secure virtual network intelligent mapping algorithm under cloud computing. Firstly, the network virtualization technology is analyzed, and a network virtualization example diagram is proposed. Then the energy consumption model and network load model of virtual network mapping problem are constructed to analyze the mapping reliability. Finally, the virtual network mapping strategy is optimized by cloud computing technology to realize the research on intelligent mapping algorithm of secure

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Dissertations / Theses on the topic "Mapping Algorithm"

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Morovič, Ján. "To develop a universal gamut mapping algorithm." Thesis, University of Derby, 1998. http://hdl.handle.net/10545/200029.

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Pomerleau, François. "Registration algorithm optimized for simultaneous localization and mapping." Mémoire, Université de Sherbrooke, 2008. http://savoirs.usherbrooke.ca/handle/11143/1465.

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Building maps within an unknown environment while keeping track of the current position is a major step to accomplish safe and autonomous robot navigation. Within the last 20 years, Simultaneous Localization And Mapping (SLAM) became a topic of great interest in robotics. The basic idea of this technique is to combine proprioceptive robot motion information with external environmental information to minimize global positioning errors. Because the robot is moving in its environment, exteroceptive data comes from different points of view and must be expressed in the same coordinate system to be

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Dunkelberg, Jr John S. "FEM Mesh Mapping to a SIMD Machine Using Genetic Algorithms." Digital WPI, 2001. https://digitalcommons.wpi.edu/etd-theses/1154.

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The Finite Element Method is a computationally expensive method used to perform engineering analyses. By performing such computations on a parallel machine using a SIMD paradigm, these analyses' run time can be drastically reduced. However, the mapping of the FEM mesh elements to the SIMD machine processing elements is an NP-complete problem. This thesis examines the use of Genetic Algorithms as a search technique to find quality solutions to the mapping problem. A hill climbing algorithm is compared to a traditional genetic algorithm, as well as a "messy" genetic algorithm. The results and co

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Liu, Zhiyong Michael. "Mapping physical topology with logical topology using genetic algorithm." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ62245.pdf.

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Curotto, Molina Franco Andreas. "Graphslam algorithm implementation for solving simultaneous localization and mapping." Tesis, Universidad de Chile, 2016. http://repositorio.uchile.cl/handle/2250/139093.

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Ingeniero Civil Eléctrico<br>SLAM (Simultaneous Localization and Mapping) es el problema de estimar la posición de un robot (u otro agente), y simultáneamente, generar un mapa de su entorno. Es considerado un concepto clave en la robótica móvil, y fundamental para alcanzar sistemas verdaderamente autónomos. Entre las muchas soluciones que se han propuesto para resolver SLAM, los métodos basados en grafos han adquirido gran interés por parte de los investigadores en los últimos años. Estas soluciones presentan varias ventajas, como la habilidad de manejar grandes cantidades de datos, y consegu

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Wang, Qing. "Development, improvement and assessment of image classification and probability mapping algorithms." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/dissertations/1622.

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Remotely sensed imagery is one of the most important data sources for large-scale and multi-temporal agricultural, forestry, soil, environmental, social and economic applications. In order to accurately extract useful thematic information of the earth surface from images, various techniques and methods have been developed. The methods can be divided into parametric and non-parametric based on the requirement of data distribution, or into global and local based on the characteristics of modeling global trends and local variability, or into unsupervised and supervised based on whether training d

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Jiang, Dayou. "An exploration of BMSF algorithm in genome-wide association mapping." Kansas State University, 2013. http://hdl.handle.net/2097/15505.

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Master of Science<br>Department of Statistics<br>Haiyan Wang<br>Motivation: Genome-wide association studies (GWAS) provide an important avenue for investigating many common genetic variants in different individuals to see if any variant is associated with a trait. GWAS is a great tool to identify genetic factors that influence health and disease. However, the high dimensionality of the gene expression dataset makes GWAS challenging. Although a lot of promising machine learning methods, such as Support Vector Machine (SVM), have been investigated in GWAS, the question of how to improve the accu

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Dash, Padmanava. "SeaWiFS Algorithm for Mapping Phycocyanin in Incipient Freshwater Cyanobacterial Blooms." Bowling Green State University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1120594611.

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Baichbal, Shashidhar. "MAPPING ALGORITHM FOR AUTONOMOUS NAVIGATION OF LAWN MOWER USING SICK LASER." Wright State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1334587886.

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Phinjaroenphan, Panu, and s2118294@student rmit edu au. "An Efficient, Practical, Portable Mapping Technique on Computational Grids." RMIT University. Computer Science and Information Technology, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080516.145808.

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Grid computing provides a powerful, virtual parallel system known as a computational Grid on which users can run parallel applications to solve problems quickly. However, users must be careful to allocate tasks to nodes properly because improper allocation of only one task could result in lengthy executions of applications, or even worse, applications could crash. This allocation problem is called the mapping problem, and an entity that tackles this problem is called a mapper. In this thesis, we aim to develop an efficient, practical, portable mapper. To study the mapping problem, researc

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Books on the topic "Mapping Algorithm"

1

Falkenhainer, Brian. The structure-mapping engine: Algorithm and examples. Dept. of Computer Science, University of Illinois at Urbana-Champaign, 1987.

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2

R, Mielke Roland, United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., and Old Dominion University. Research Foundation., eds. Algorithm to Architecture Mapping Model (ATAMM) multicomputer operating system functional specification. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1990.

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Menemenlis, Dimitris. Adaptation of a fast optimal interpolation algorithm to the mapping of oceanographic data. National Aeronautics and Space Administration, 1997.

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R, Patel Rakesh, and Langley Research Center, eds. Resource utilization model for the algorithm to architecture mapping model: Progress report for the period ended June 30, 1993. Dept. of Electrical & Computer Engineering, College of Engineering & Technology, Old Dominion University, 1993.

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Anderson, Jay Martin. Algorithms for computer cartography. Franklin and Marshall College, 1998.

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Lee, P. Mapping nested loop algorithms into multi-dimensional systolic arrays. Courant Institute of Mathematical Sciences, New York University, 1988.

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Center, Langley Research, ed. A parallel algorithms for mapping pipelined and parallel computations. NASA Langley Research Center, 1988.

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Mester, D. Discrete optimization for TSP-like genome mapping problems. Nova Science Publishers, 2010.

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Sokol'skaya, Elena, and Boris Kochurov. Geoecology of the city: models of environmental quality. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1205961.

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The monograph examines the features of studying the geoecological state of urbanized territories, reveals the use of integrated assessment and mapping in urban diagnostics, and finds a solution to geoecological problems on the example of world cities that are leading in the rating for quality of life. The components of an information and analytical model of the urban environment for assessing the geoecological situation are described; an algorithm for a comprehensive study of the geoecological state aimed at an adequate assessment of the quality of the urban environment. Special attentio

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Center, Langley Research, ed. Efficient algorithms for dilated mappings of binary trees. National Aeronautics and Space Administration, Langley Research Center, 1990.

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Book chapters on the topic "Mapping Algorithm"

1

Zhao, Jie, Wenlei Wang, Qiuming Cheng, and Yunqing Shao. "Nonlinear Mapping Algorithm." In Encyclopedia of Mathematical Geosciences. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-85040-1_226.

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Zhao, Jie, Wenlei Wang, Qiuming Cheng, and Yunqing Shao. "Nonlinear Mapping Algorithm." In Encyclopedia of Mathematical Geosciences. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-26050-7_226-1.

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Ewald, Roland. "Selection Mapping Generation." In Automatic Algorithm Selection for Complex Simulation Problems. Vieweg+Teubner Verlag, 2012. http://dx.doi.org/10.1007/978-3-8348-8151-9_6.

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Boillat, Jacques E., and Peter G. Kropf. "A fast distributed mapping algorithm." In CONPAR 90 — VAPP IV. Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-53065-7_119.

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Mahdi, Tamer S., and Robert E. Mercer. "A Lexical Functional Mapping Algorithm." In Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47922-8_25.

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Wang, Xiao-guang, Xiang-wei Zheng, and Dian-jie Lu. "A Heuristic Virtual Network Mapping Algorithm." In Intelligent Computing Methodologies. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09339-0_40.

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Mascioli, F. M. Frattale, and G. Martinelli. "A Constructive Algorithm for Binary Mapping." In ICANN ’93. Springer London, 1993. http://dx.doi.org/10.1007/978-1-4471-2063-6_215.

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He, Ping, Tianyu Jing, Xiaohua Xu, Lei Zhang, and Huihui Lin. "Supervised Isometric Mapping Based Classification Algorithm." In Lecture Notes in Computer Science. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46257-8_33.

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Veluri, Ravi Kishore, S. Rama Sree, A. Vanathi, G. Aparna, and S. Prasanth Vaidya. "Hand Gesture Mapping Using MediaPipe Algorithm." In Proceedings of Third International Conference on Communication, Computing and Electronics Systems. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8862-1_39.

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Kao, Ming-Yang, Jared Samet, and Wing-Kin Sung. "The Enhanced Double Digest Problem for DNA Physical Mapping." In Algorithm Theory - SWAT 2000. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44985-x_33.

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Conference papers on the topic "Mapping Algorithm"

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Yin, Jiazhao, Yuning Chen, Yudong Xu, Zhanpeng Li, and Xiang Lin. "Multi-satellite task planning algorithm based on target clustering." In Fourth International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2025), edited by Jinjian Wu and Juanle Wang. SPIE, 2025. https://doi.org/10.1117/12.3066859.

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Liu, Gengchen, Liang Jiang, Guoqiang Wu, Kun Huang, and Haohui Sun. "Aerospace Heterogeneous Image Matching Algorithm Based on Spatiotemporal Continuity." In 2025 6th International Conference on Geology, Mapping and Remote Sensing (ICGMRS). IEEE, 2025. https://doi.org/10.1109/icgmrs66001.2025.11065899.

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Wang, Shen, and Yanping Liang. "Improved highway abandoned objects detection algorithm of YOLOv5." In Second International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2025), edited by Fabio Tosti and Román Alvarez. SPIE, 2025. https://doi.org/10.1117/12.3067662.

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Wu, Jingxuan, Biquan Chen, Rui Zhang, Minmin Li, and Liangdong He. "Foggy image enhancement algorithm based on dynamic weighting." In Second International Conference on Remote Sensing, Mapping and Image Processing (RSMIP 2025), edited by Fabio Tosti and Román Alvarez. SPIE, 2025. https://doi.org/10.1117/12.3067695.

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Osama, Hoda, Yasser Omar, and Amr Badr. "Mapping sorting algorithm." In 2016 SAI Computing Conference (SAI). IEEE, 2016. http://dx.doi.org/10.1109/sai.2016.7556025.

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Hegde, Kartik, Po-An Tsai, Sitao Huang, Vikas Chandra, Angshuman Parashar, and Christopher W. Fletcher. "Mind mappings: enabling efficient algorithm-accelerator mapping space search." In ASPLOS '21: 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems. ACM, 2021. http://dx.doi.org/10.1145/3445814.3446762.

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Kraut, Jay. "A relative mapping algorithm." In 2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2013. http://dx.doi.org/10.1109/ccece.2013.6567715.

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Ismail, Hesham, and Balakumar Balachandran. "Feature Extraction Algorithm Fusion for SONAR Sensor Data Based Environment Mapping." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-37116.

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Mobile platforms that make use of concurrent localization and mapping algorithms have industrial applications for autonomous inspection and maintenance, such as the inspection of flaws and defects in oil pipelines and storage tanks. An important component of these algorithms is feature extraction, which involves detection of significant features that represent the environment. For example, points and lines can be used to represent features such as corners, edges, and walls. Feature extraction algorithms make use of relative position and angle data from sensor measurements gathered as the mobil

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Tan, Junlang, Yihua Huang, and Kai Wang. "Logarithmic Tone Mapping Algorithm Based on Block Mapping Fusion." In 2018 International Conference on Audio, Language and Image Processing (ICALIP). IEEE, 2018. http://dx.doi.org/10.1109/icalip.2018.8455806.

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Gorgoteanu, Damian, Lucian Stefanita Grigore, and Cristian Molder. "Mapping algorithm using SWARM robots." In 2021 13th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). IEEE, 2021. http://dx.doi.org/10.1109/ecai52376.2021.9515072.

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Reports on the topic "Mapping Algorithm"

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Champlin, Craig, and John P. H. Steele. DTPH56-14H-CAP06 Pipeline Assessment through 4-Dimensional Anomaly Detection and Characterization. Pipeline Research Council International, Inc. (PRCI), 2016. http://dx.doi.org/10.55274/r0011766.

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The team intended to develop two algorithms for matching anomalies across coincident internal pipeline inspections to assess corrosion growth rates. The first algorithm would match boxed anomalies. The second algorithm would match raw signals. The goal for each algorithm is slightly different. The boxed algorithm is intended to do a complete mapping of individual called-out anomalies from one inspection to the next. The raw signal algorithm velocity corrects and aligns raw inspections signals.

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Scannapieco, Anthony J. An Adaptive Mesh Algorithm: Mapping the Mesh Variables. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1304744.

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Pattipati, Krishna R., Peter B. Luh, Rong-Tay Lee, Samir Shah, and Somanth Deb. BM/C(3) Algorithm Mapping Onto Concurrent Processors. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada207877.

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Hendrickson, B., and R. Leland. An improved spectral graph partitioning algorithm for mapping parallel computations. Office of Scientific and Technical Information (OSTI), 1992. http://dx.doi.org/10.2172/6970738.

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Alwan, Iktimal, Dennis D. Spencer, and Rafeed Alkawadri. Comparison of Machine Learning Algorithms in Sensorimotor Functional Mapping. Progress in Neurobiology, 2023. http://dx.doi.org/10.60124/j.pneuro.2023.30.03.

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Objective: To compare the performance of popular machine learning algorithms (ML) in mapping the sensorimotor cortex (SM) and identifying the anterior lip of the central sulcus (CS). Methods: We evaluated support vector machines (SVMs), random forest (RF), decision trees (DT), single layer perceptron (SLP), and multilayer perceptron (MLP) against standard logistic regression (LR) to identify the SM cortex employing validated features from six-minute of NREM sleep icEEG data and applying standard common hyperparameters and 10-fold cross-validation. Each algorithm was tested using vetted feature

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Steensland, Johan, and Jaideep Ray. A heuristic re-mapping algorithm reducing inter-level communication in SAMR applications. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/918288.

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Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7598158.bard.

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Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no

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O'Neill, Francis, Kristofer Lasko, and Elena Sava. Snow-covered region improvements to a support vector machine-based semi-automated land cover mapping decision support tool. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45842.

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This work builds on the original semi-automated land cover mapping algorithm and quantifies improvements to class accuracy, analyzes the results, and conducts a more in-depth accuracy assessment in conjunction with test sites and the National Land Cover Database (NLCD). This algorithm uses support vector machines trained on data collected across the continental United States to generate a pre-trained model for inclusion into a decision support tool within ArcGIS Pro. Version 2 includes an additional snow cover class and accounts for snow cover effects within the other land cover classes. Overa

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Cowell, Luke, Alejandro Camou, Ivan Carlos, and Dustin Truesdel. PR-283-16201-R01 Improved SoLoNOx Taurus 60 Control Algorithm to Reduce Part Load Emissions. Pipeline Research Council International, Inc. (PRCI), 2018. http://dx.doi.org/10.55274/r0011510.

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An executed NDA is required from Solar Turbines to have access to this document. The low load control algorithm for Solar Turbines' TaurusTM 60-7802S has been modified and evaluated in a field trial at the TransCanada Glenville Compressor Station. The algorithm has been modified to extend the bleed valve operating range to lower engine speed settings covering operation from idle to 50% load. The pilot fuel schedule has also been optimized with the new bleed valve schedule. The new control algorithm is designated as Enhanced Emissions Control (EEC). A Mobile Emissions Lab (MEL) and three site v

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Cowell and Roesch. PR-283-14204-R01 SoLoNOx Low Load Controls to Reduce Emissions for Less Restrictive Load Following. Pipeline Research Council International, Inc. (PRCI), 2016. http://dx.doi.org/10.55274/r0011016.

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Abstract:

A Mobile Emissions Lab (MEL) and two site visits for extensive low load emissions mapping were used to document the emissions performance of the test unit over a 10 month period from June 2015 to April 2016. Data was collected over a wide ambient temperature range from 35 to 108?F. The field trial has demonstrated that the new algorithm results in a significant reduction in NOx, CO and UHC emissions from idle to 50% load. Reductions in CO and UHC emission of 50 to 99% were demonstrated from idle to 50% load. NOx emissions reductions were slightly less ranging from 20 to 75% from idle to 50% lo

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